Srini Narayanan

6.1k total citations · 2 hit papers
34 papers, 3.1k citations indexed

About

Srini Narayanan is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Information Systems. According to data from OpenAlex, Srini Narayanan has authored 34 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 8 papers in Experimental and Cognitive Psychology and 7 papers in Information Systems. Recurrent topics in Srini Narayanan's work include Semantic Web and Ontologies (13 papers), Natural Language Processing Techniques (13 papers) and Topic Modeling (11 papers). Srini Narayanan is often cited by papers focused on Semantic Web and Ontologies (13 papers), Natural Language Processing Techniques (13 papers) and Topic Modeling (11 papers). Srini Narayanan collaborates with scholars based in United States, United Kingdom and Switzerland. Srini Narayanan's co-authors include Sheila A. McIlraith, Jerry R. Hobbs, Katia Sycara, Honglei Zeng, Mark Burstein, Ora Lassila, Massimo Paolucci, Terry R. Payne, David L. Martin and Anupriya Ankolekar and has published in prestigious journals such as Neurocomputing, Cognitive Science and Computer Networks.

In The Last Decade

Srini Narayanan

34 papers receiving 2.7k citations

Hit Papers

DAML-S: semantic markup for web services 2001 2026 2009 2017 2001 2002 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Srini Narayanan United States 14 2.1k 2.0k 903 843 246 34 3.1k
Lynn Andrea Stein United States 18 862 0.4× 1.5k 0.7× 209 0.2× 508 0.6× 38 0.2× 59 2.3k
Mark Burstein United States 15 2.0k 0.9× 1.7k 0.9× 713 0.8× 826 1.0× 22 0.1× 52 2.6k
Andrew Begel United States 33 2.2k 1.0× 783 0.4× 285 0.3× 556 0.7× 90 0.4× 101 3.8k
Ronald J. Brachman United States 24 706 0.3× 2.9k 1.4× 167 0.2× 936 1.1× 81 0.3× 49 3.6k
André van der Hoek United States 34 2.6k 1.2× 1.6k 0.8× 248 0.3× 808 1.0× 26 0.1× 195 3.6k
Clarence A. Ellis United States 22 1.3k 0.6× 782 0.4× 991 1.1× 970 1.2× 19 0.1× 65 3.4k
Philipp Cimiano Germany 34 1.5k 0.7× 4.0k 2.0× 111 0.1× 325 0.4× 54 0.2× 248 4.7k
Kristian J. Hammond United States 22 1.2k 0.6× 1.8k 0.9× 80 0.1× 356 0.4× 96 0.4× 113 3.0k
Vladan Devedžić Serbia 27 1.0k 0.5× 1.3k 0.6× 310 0.3× 253 0.3× 21 0.1× 125 2.3k
Terry R. Payne United Kingdom 21 1.9k 0.9× 1.6k 0.8× 619 0.7× 934 1.1× 11 0.0× 131 2.7k

Countries citing papers authored by Srini Narayanan

Since Specialization
Citations

This map shows the geographic impact of Srini Narayanan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Srini Narayanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srini Narayanan more than expected).

Fields of papers citing papers by Srini Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Srini Narayanan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Srini Narayanan. The network helps show where Srini Narayanan may publish in the future.

Co-authorship network of co-authors of Srini Narayanan

This figure shows the co-authorship network connecting the top 25 collaborators of Srini Narayanan. A scholar is included among the top collaborators of Srini Narayanan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Srini Narayanan. Srini Narayanan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Nadler, Ethan O., et al.. (2025). Statistical or Embodied? Comparing Colorseeing, Colorblind, Painters, and Large Language Models in Their Processing of Color Metaphors. Cognitive Science. 49(7). e70083–e70083. 1 indexed citations
2.
Eisenschlos, Julian Martin, et al.. (2022). MiQA: A Benchmark for Inference on Metaphorical Questions. 373–381. 2 indexed citations
3.
Baldridge, Jason, Tania Bedrax-Weiss, Srini Narayanan, et al.. (2018). Points, Paths, and Playscapes: Large-scale Spatial Language Understanding Tasks Set in the Real World. 46–52. 7 indexed citations
4.
Shutova, Ekaterina, et al.. (2016). Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning. Computational Linguistics. 43(1). 71–123. 37 indexed citations
5.
Schilling, Malte & Srini Narayanan. (2013). Communicating with Executable Action Representations. PUB – Publications at Bielefeld University (Bielefeld University). 1 indexed citations
6.
Makin, Joseph G. & Srini Narayanan. (2013). A HYBRID-SYSTEM MODEL OF THE COAGULATION CASCADE: SIMULATION, SENSITIVITY, AND VALIDATION. Journal of Bioinformatics and Computational Biology. 11(5). 1342004–1342004. 6 indexed citations
7.
Finlayson, Mark A., Pablo Gervás, Erik T. Mueller, Srini Narayanan, & Patrick Henry Winston. (2010). Preface: Computational Models of Narrative. National Conference on Artificial Intelligence. 2 indexed citations
8.
Lakoff, George & Srini Narayanan. (2010). Toward a Computational Model of Narrative. eScholarship (California Digital Library). 13 indexed citations
9.
Bergen, Benjamin K., Shane Lindsay, Teenie Matlock, & Srini Narayanan. (2007). Spatial and Linguistic Aspects of Visual Imagery in Sentence Comprehension. Cognitive Science. 31(5). 733–764. 173 indexed citations
10.
Lindsay, Shane, et al.. (2007). Spatial and Linguistic Aspects of Visual Imagery. 1 indexed citations
11.
Fillmore, Charles J., Srini Narayanan, & Collin F. Baker. (2006). What can linguistics contribute to event extraction. Scandinavian Journal of Clinical and Laboratory Investigation. 78(3). 230–235. 6 indexed citations
12.
Scheffczyk, Jan & Srini Narayanan. (2006). Ontology-based Reasoning about Lexical Resources. 73(5). 1117–1119. 27 indexed citations
13.
Narayanan, Srini & Sanda M. Harabagiu. (2004). Answering Questions Using Advanced Semantics and Probabilistic Inference. North American Chapter of the Association for Computational Linguistics. 10–16. 4 indexed citations
14.
Narayanan, Srini & Sanda M. Harabagiu. (2004). Question answering based on semantic structures. 693–es. 128 indexed citations
15.
Narayanan, Srini. (2003). The role of cortico-basal-thalamic loops in cognition: a computational model and preliminary results. Neurocomputing. 52-54. 605–614. 7 indexed citations
16.
Narayanan, Srini & Sheila A. McIlraith. (2002). Simulation, verification and automated composition of web services. 215 indexed citations
17.
Shastri, Lokendra, et al.. (2002). A Connectionist Encoding of Parameterized Schemas and Reactive Plans. 7 indexed citations
18.
Denker, Grit, Jerry R. Hobbs, David Martín, Srini Narayanan, & Richard Waldinger. (2001). Accessing information and services on the DAML enabled web. International Semantic Web Conference. 67–77. 20 indexed citations
19.
Ankolekar, Anupriya, Mark Burstein, Jerry R. Hobbs, et al.. (2001). DAML-S: semantic markup for web services. 411–430. 1511 indexed citations breakdown →
20.
Feldman, Jerome A., George Lakoff, David Bailey, et al.. (1996). L0-The first five years of an automated language acquisition project. Artificial Intelligence Review. 10(1-2). 103–129. 27 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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